function perfect_foresight_solver() % Computes deterministic simulations % % INPUTS % None % % OUTPUTS % none % % ALGORITHM % % SPECIAL REQUIREMENTS % none % Copyright (C) 1996-2014 Dynare Team % % This file is part of Dynare. % % Dynare is free software: you can redistribute it and/or modify % it under the terms of the GNU General Public License as published by % the Free Software Foundation, either version 3 of the License, or % (at your option) any later version. % % Dynare is distributed in the hope that it will be useful, % but WITHOUT ANY WARRANTY; without even the implied warranty of % MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the % GNU General Public License for more details. % % You should have received a copy of the GNU General Public License % along with Dynare. If not, see . global M_ options_ oo_ if options_.stack_solve_algo < 0 || options_.stack_solve_algo > 7 error('PERFECT_FORESIGHT_SOLVER: stack_solve_algo must be between 0 and 7') end if ~options_.block && ~options_.bytecode && options_.stack_solve_algo ~= 0 ... && options_.stack_solve_algo ~= 6 && options_.stack_solve_algo ~= 7 error('PERFECT_FORESIGHT_SOLVER: you must use stack_solve_algo=0 or stack_solve_algo=6 when not using block nor bytecode option') end if options_.block && ~options_.bytecode && options_.stack_solve_algo == 5 error('PERFECT_FORESIGHT_SOLVER: you can''t use stack_solve_algo = 5 without bytecode option') end if (options_.block || options_.bytecode) && options_.stack_solve_algo == 6 error('PERFECT_FORESIGHT_SOLVER: you can''t use stack_solve_algo = 6 with block or bytecode option') end if isoctave && options_.stack_solve_algo == 2 error('PERFECT_FORESIGHT_SOLVER: you can''t use stack_solve_algo = 2 under Octave') end if isempty(oo_.endo_simul) || any(size(oo_.endo_simul) ~= [ M_.endo_nbr, M_.maximum_lag+options_.periods+M_.maximum_lead ]) error('PERFECT_FORESIGHT_SOLVER: ''oo_.endo_simul'' has wrong size. Did you run ''perfect_foresight_setup'' ?') end if isempty(oo_.exo_simul) || any(size(oo_.exo_simul) ~= [ M_.maximum_lag+options_.periods+M_.maximum_lead, M_.exo_nbr ]) error('PERFECT_FORESIGHT_SOLVER: ''oo_.exo_simul'' has wrong size. Did you run ''perfect_foresight_setup'' ?') end if isempty(options_.scalv) || options_.scalv == 0 options_.scalv = oo_.steady_state; end options_.scalv= 1; if options_.debug model_static = str2func([M_.fname,'_static']); for ii=1:size(oo_.exo_simul,1) [residual(:,ii)] = model_static(oo_.steady_state, oo_.exo_simul(ii,:),M_.params); end problematic_periods=find(any(isinf(residual)) | any(isnan(residual)))-M_.maximum_endo_lag; if ~isempty(problematic_periods) period_string=num2str(problematic_periods(1)); for ii=2:length(problematic_periods) period_string=[period_string, ', ', num2str(problematic_periods(ii))]; end fprintf('\n\nWARNING: Value for the exogenous variable(s) in period(s) %s inconsistent with the static model.\n',period_string); fprintf('WARNING: Check for division by 0.\n') end end % Effectively compute simulation, possibly with homotopy if options_.no_homotopy simulation_core; else exosim = oo_.exo_simul; exoinit = repmat(oo_.exo_steady_state',M_.maximum_lag+options_.periods+M_.maximum_lead,1); endosim = oo_.endo_simul; endoinit = repmat(oo_.steady_state, 1,M_.maximum_lag+options_.periods+M_.maximum_lead); current_weight = 0; % Current weight of target point in convex combination step = 1; success_counter = 0; while (step > options_.dynatol.x) new_weight = current_weight + step; % Try this weight, and see if it succeeds if new_weight >= 1 new_weight = 1; % Don't go beyond target point step = new_weight - current_weight; end % Compute convex combination for exo path and initial/terminal endo conditions % But take care of not overwriting the computed part of oo_.endo_simul oo_.exo_simul = exosim*new_weight + exoinit*(1-new_weight); endocombi = endosim*new_weight + endoinit*(1-new_weight); oo_.endo_simul(:,1:M_.maximum_endo_lag) = endocombi(:,1:M_.maximum_endo_lag); oo_.endo_simul(:,(end-M_.maximum_endo_lead):end) = endocombi(:,(end-M_.maximum_endo_lead):end); saved_endo_simul = oo_.endo_simul; simulation_core; if oo_.deterministic_simulation.status == 1 current_weight = new_weight; if current_weight >= 1 break end success_counter = success_counter + 1; if success_counter >= 3 success_counter = 0; step = step * 2; disp([ 'Homotopy step succeeded, doubling step size (completed ' sprintf('%.1f', current_weight*100) '%, step size ' sprintf('%.3g', step) ')' ]) else disp([ 'Homotopy step succeeded (completed ' sprintf('%.1f', current_weight*100) '%, step size ' sprintf('%.3g', step) ')' ]) end else oo_.endo_simul = saved_endo_simul; success_counter = 0; step = step / 2; disp([ 'Homotopy step failed, halving step size (completed ' sprintf('%.1f', current_weight*100) '%, step size ' sprintf('%.3g', step) ')' ]) end end end if oo_.deterministic_simulation.status == 1 disp('Perfect foresight solution found.') else warning('Failed to solve perfect foresight model') end dyn2vec; if isnan(options_.initial_period) initial_period = dates(1,1); else initial_period = options_.initial_period; end ts = dseries(transpose(oo_.endo_simul),initial_period,cellstr(M_.endo_names)); assignin('base', 'Simulated_time_series', ts); end function simulation_core() global M_ oo_ options_ if(options_.block) if(options_.bytecode) [info, oo_.endo_simul] = bytecode('dynamic'); if info == 1 oo_.deterministic_simulation.status = 0; else oo_.deterministic_simulation.status = 1; end mexErrCheck('bytecode', info); else eval([M_.fname '_dynamic']); end else if(options_.bytecode) [info, oo_.endo_simul]=bytecode('dynamic'); if info == 1 oo_.deterministic_simulation.status = 0; else oo_.deterministic_simulation.status = 1; end; mexErrCheck('bytecode', info); else if M_.maximum_endo_lead == 0 % Purely backward model sim1_purely_backward; elseif M_.maximum_endo_lag == 0 % Purely forward model sim1_purely_forward; else % General case if options_.stack_solve_algo == 0 sim1; elseif options_.stack_solve_algo == 6 sim1_lbj; elseif options_.stack_solve_algo == 7 periods = options_.periods; if ~isfield(options_.lmmcp,'lb') [lb,ub,pfm.eq_index] = get_complementarity_conditions(M_); options_.lmmcp.lb = repmat(lb,periods,1); options_.lmmcp.ub = repmat(ub,periods,1); end y = oo_.endo_simul; y0 = y(:,1); yT = y(:,periods+2); z = y(:,2:periods+1); illi = M_.lead_lag_incidence'; [i_cols,~,i_cols_j] = find(illi(:)); illi = illi(:,2:3); [i_cols_J1,~,i_cols_1] = find(illi(:)); i_cols_T = nonzeros(M_.lead_lag_incidence(1:2,:)'); [y,info] = dynare_solve(@perfect_foresight_problem,z(:),1, ... str2func([M_.fname '_dynamic']),y0,yT, ... oo_.exo_simul,M_.params,oo_.steady_state, ... options_.periods,M_.endo_nbr,i_cols, ... i_cols_J1, i_cols_1, i_cols_T, i_cols_j, ... M_.NNZDerivatives(1)); oo_.endo_simul = [y0 reshape(y,M_.endo_nbr,periods) yT]; if info == 1 oo_.deterministic_simulation.status = 0; else oo_.deterministic_simulation.status = 1; end; end end end end end